Physics Department, University of Malta, Msida MSD 2080, Malta

In this paper, we have studied in depth the effect of Etna volcanic ash clouds on the Maltese Islands. Research was carried out to gather information about Etna's eruptions that impacted the Maltese Islands, starting with historical eruptions dating back to the 14th century continuing to present day. A statistical approach was utilized to provide tephra deposit load and ash concentration using PUFF — a model which simulates the transport, dispersion and sedimentation of volcanic ash. Three different eruptive scenarios that characterize Etna's recent activity were considered; the first scenario representing the 2001 eruption (Sc1), the second scenario representing the July 1998 eruption (Sc2) whilst the third scenario represents the recent activity in 2011– 2012 (Sc3). We found that the time taken for the volcanic ash cloud to reach the Maltese Islands, when the wind direction is toward the south-west ranges from 4 to 6 h. The probability that an Etna volcanic cloud reaches Malta during an eruption is about 15% per annum. The now calibrated model may be now used to produce deposit load and cumulative columnar load (i.e. summation from maximum height of volcanic cloud to ground) of volcanic ash in atmosphere for the Maltese area and help the aviation authorities and Malta airport to make decisions during Etna eruptions. This will be of direct use to local communities and aviation.

Following a recent paperwe useweak-motionwaveforms to calibrate a model for the prediction of earthquake-induced ground-motion in Taiwan, in the 0.25–5.0 Hz frequency range, valid up to Mw 7.6. The excitation/attenuation model is given in terms of frequency-dependent seismic wave attenuation, Qs(f ), geometrical spreading, g(r), amagnitude-dependent stress parameters σ for the excitation terms, and a site term for each seismic station used in the study. A set of weak-motion data was gathered from about 170 aftershocks of the Chi–Chi earthquake, Mw 7.6, of 1999 September 20, (17:47 UTC), recorded by 10 broad-band seismic stations. The moment magnitudes of the registered aftershocks ranged from Mw 3.0 to 6.5, and the hypocentral distances from a few kilometres to about 250 km. A frequency-dependent crustal quality factor, Q(f ) = 350f 0.32, was obtained, to be coupled with the geometrical spreading function g (r ) = ⎧⎪ ⎪⎨⎪ ⎪⎩ r−1.2 1 < r < 10 km r−0.7 10 < r < 40 km r−1.0 40 < r < 80 km r−0.5 r > 80 km. Earthquake-related excitation spectra were calibrated over our empirical results by using a magnitude-dependent Brune model with a stress drop value of σ = 8.0 ± 1.0 MPa for the largest event of Mw 6.5 in our data set and with a near surface attenuation parameter of κ = 0.05 s. Results on region-specific crustal attenuation and source scaling were used to generate stochastic simulations both for point-source and extended-fault ruptures through the computer codes: Stochastic Model SIMulation, SMSIM and Extended-FaultModel Simulation, EXSIM. The absolute peak ground accelerations (PGA), peak ground velocities (PGV) and 5 per centdamped Spectral Accelerations (SA) at three different frequencies, 0.33 Hz, 1.0 Hz and 3.0 Hz for several magnitudes and distance ranges were predicted at large magnitudes, well beyond magnitudeMw 6.5, the upper limit for the events of ourweak-motion data set. The performance of the stochastic model was then tested against the strong-motion data recorded during the Mw 7.6 Chi–Chi earthquake, and against several other empirical ground-motion models.